Recent advancements in artificial intelligence (AI) enable the rapid collection and organization of academic research with the push of a button, prompting a reevaluation of the role and value of human-generated systematic literature reviews (SLRs). In this editorial, we explore the value of the human element in producing SLRs, a method originally designed to reduce human bias in literature synthesis. Throughout the three stages of an SLR-design, study collection and selection, and interpretation and communication-we argue that the human element is not just a potential source of bias but also an essential contributor of value. The value of human-generated SLRs lies in (1) formulating the right questions, (2) strategic inefficiency in literature search and selection, and (3) individualized problematizing and theorizing. To better leverage the human element in SLRs, we call for new forms of hybrid SLRs that combine traditional systematic review methods with empirical fieldwork.

Abstract Since 2015, there was a significant surge of interest in employee misfit. These studies demonstrate that although misfit is generally associated with negative outcomes such as organizational exit, social isolation, and depressive states, it can also be viewed more positively as an opportunity for job crafting, growth, and development. In these studies, misfit has been conceptualized, defined, and measured in a myriad of different ways making the interpretation of results problematic. This systematic review investigates how scholars have approached misfit with the goals of documenting and organizing the various ways it has been conceptualized and measured to highlight the main themes and forms of empirical misfit research. The systematic review surfaced 107 studies in 91 papers investigating workplace misfit within the domain of person-environment fit. Close analysis of the design and construction of these studies reveals that misfit has largely been conceptualized atomistically or as value incongruence and there is considerable variation in the way that researchers have defined the concept. It has mainly been measured using atomistic and molar measures rather than molecular ones, which are more suited to misfit investigation. The paper ends with a discussion of the elusiveness of misfit with an argument that it is an umbrella concept beyond definition. Instead, researchers take perspectives on the topic and six different perspectives of employee misfit are identified and defined. Avenues for future research are outlined for each perspective. There is also a discussion of the methodological challenges currently limiting misfit research.

Abstract Artificial intelligence (AI) has made remarkable progress in the past decade. Despite the plethora of AI research, we lack an accrued overview of the extent to which management research uses AI algorithms. The context, purpose, and type of AI used in previous work remain unknown, though this information is critical to coordinating, extending, and strengthening the use of AI. We address this knowledge gap with a systematic literature review (SLR), focusing on 12 leading information systems (IS) journals and leveraging a customized generative pre-trained transformer (GPT) in our analyses. We propose a conceptual framework comprising eight dimensions to categorize our findings in terms of application areas, methods, and algorithms of applied AI, mitigating the lack of a concise AI taxonomy. Thus, we identify and discuss trends, outline underrepresented algorithms with significant potential, and derive research avenues. We extend the literature with a conceptual overview that may serve as a building block for theory building and further exploration of the evolving AI research domain.

Abstract Defining the deal value in mergers and acquisitions is inherently complex and often constitutes an inflection point for the parties involved. By paying part of the deal value at a later stage according to predefined goals, earnouts are intended to alleviate information asymmetries and help bridge valuation differences. Despite their wide application in practice, research on earnouts remains fragmented. This study presents the first systematic literature review of earnouts, mapping the scattered research landscape by analyzing 64 papers published between 1970 and 2023. The review categorizes the body of earnout research into three distinct streams: the motives for employing earnouts, their implications, and the nuances of their contractual arrangements. Based on this synthesis, research gaps are identified that present a comprehensive road map for future research. This study enables investors to employ earnouts more successfully and guides scholars to pursue further earnout research based on its holistic overview.

Entrepreneurship through acquisition (ETA) is gaining momentum as a viable alternative to starting a company on one’s own. However, despite its growing practical relevance, scholarly work about ETA is scarce and has not been comprehensively reviewed. To address this gap, we conduct a systematic review of entrepreneurship literature by identifying studies that examine ETA and its outcomes. Our review methodology was developed based on established guidelines for systematic reviews and protocols, which informed our scoping review process and analytical approach. Searches were conducted on three electronic databases, and inclusion/exclusion criteria were applied. For inclusion, studies must examine an entrepreneurial perspective in buying into a company. Quantitative and qualitative data were extracted for thematic analysis and descriptive statistics. ETA is an entrepreneurship model with growing appeal and relevance in practice but limited academic evidence. While there is extensive research on leveraged buyouts and family-external succession, evidence specifically on ETA is still lacking. In particular, knowledge about the entrepreneurial intent that makes ETA unique is absent from the evidence base. As ETA gains momentum, entrepreneurs need to understand the unique properties, the various approaches, and the upsides and eventual downsides of acquiring a business instead of starting one from scratch. The present work may serve as a starting point for future research as we scope existing evidence on the archetype of ETA and identify a definition, available models, and a process archetype.

The service productivity literature has grown remarkably over the last two decades and has gathered substantial knowledge. However, with the gradual acceleration of knowledge production about service productivity, the collective evidence becomes more fragmented and interdisciplinary. The purpose of this literature review is to systematically identify and analyze 190 publications focusing on service productivity to link previously dispersed studies as a next step in theory development. By clustering existing service productivity research into macroeconomic, mesoeconomic, and microeconomic dimensions, our review reveals that much progress has been made in advancing the open-ended theory of optimal service productivity. Reviewing key insights from the existing literature, we show that the majority of service productivity research adopts a one-sided industrial perspective that primarily focuses on firm productivity. Although valuable, these studies most often leave out consumers’ time and effort, neglecting the value of consumer-generated input. Thus, the present research offers a new conceptualization of service productivity by emphasizing it as an open and customer-inclusive process that transcends the service producer–customer divide. Finally, we contribute a set of propositions. Within these propositions, we identify beneficial conditions and means for firms to improve service productivity. In sum, the article provides policymakers, researchers, and practitioners with valuable guidance for developing means to generate positive effects in a service economy that lacks productivity.